Abstract:

The problem of students’ understanding and mastering mathematics is currently one of the most emphasized topics of expert public discussion. Teaching Mathematics is taking place in rapidly changing conditions. It is necessary to look for optimal didactic and educational solutions encompassing goals and contents as well as forms and teaching methods allowing for preparing students personal development and development of society.

Mathematics is a specific subject. To have a number of relevant information, to know the facts or isolated terms, to recall mathematical sentences, definitions or formulas is only the first step. The cardinal necessity is to understand their mutual context, which is the only source of true knowledge also applicable in reality. If we want to progress in the field of teaching mathematics, we need to use the methods, forms and means of teaching, which would motivate students to be active, creative and engaged.

Well organized mathematical education facilitates logical thinking and expressing ideas, organizing own work, planning and organizing the learning process, collaboration and responsibility; it prepares for life in a modern world and enables to perform many jobs.

In this article we present the results of pedagogical experiment, which has verified the effectiveness of three teaching methods used to teach selected units of mathematics. For the purposes of the experiment we randomly chose the group of 105 students from of the first year students of the Faculty of Security Engineering, University of Zilina in Zilina.

Regarding the obtained results the statistical methods of the single-factor analysis of variance for balanced model and Duncan’s multiple range test were used to specify the most effective teaching method. The results of the experiment unambiguously confirm the teaching by problems solving methods the most effective method in the teaching of mathematics.

Keywords:

Pedagogical experiment, teaching method, visualization methods, problem solving methods, one-factor analysis of variance, Duncan´s multiple range test.